Department of Computational Biology, Cornell University, Ithaca, NY, 14853, USA.
Department of Biology, Stanford University, Stanford, CA, 94305, USA.
Eur J Hum Genet. 2023 Nov;31(11):1283-1290. doi: 10.1038/s41431-023-01430-9. Epub 2023 Aug 11.
In many forensic settings, identity of a DNA sample is sought from poor-quality DNA, for which the typical STR loci tabulated in forensic databases are not possible to reliably genotype. Genome-wide SNPs, however, can potentially be genotyped from such samples via next-generation sequencing, so that queries can in principle compare SNP genotypes from DNA samples of interest to STR genotype profiles that represent proposed matches. We use genetic record-matching to evaluate the possibility of testing SNP profiles obtained from poor-quality DNA samples to identify exact and relatedness matches to STR profiles. Using simulations based on whole-genome sequences, we show that in some settings, similar match accuracies to those seen with full coverage of the genome are obtained by genetic record-matching for SNP data that represent 5-10% genomic coverage. Thus, if even a fraction of random genomic SNPs can be genotyped by next-generation sequencing, then the potential may exist to test the resulting genotype profiles for matches to profiles consisting exclusively of nonoverlapping STR loci. The result has implications in relation to criminal justice, mass disasters, missing-person cases, studies of ancient DNA, and genomic privacy.
在许多法医鉴定环境中，需要从低质量 DNA 中寻找 DNA 样本的身份，对于这些 DNA 样本，通常无法可靠地对法医数据库中列出的典型 STR 基因座进行基因分型。然而，全基因组 SNPs 可以通过下一代测序技术对这些样本进行潜在的基因分型，因此原则上可以将感兴趣的 DNA 样本中的 SNP 基因型与代表拟议匹配的 STR 基因型图谱进行比较。我们使用遗传记录匹配来评估从低质量 DNA 样本中获得的 SNP 图谱进行测试的可能性，以识别与 STR 图谱的精确和相关性匹配。基于全基因组序列的模拟表明，在某些情况下，通过遗传记录匹配获得的 SNP 数据的匹配准确性与全基因组覆盖时相似，代表 5-10%的基因组覆盖。因此，如果通过下一代测序可以对随机基因组 SNP 的一部分进行基因分型，那么就有可能对由非重叠 STR 基因座组成的图谱进行测试，以测试由此产生的基因型图谱是否与图谱匹配。这一结果对刑事司法、大规模灾难、失踪人员案件、古代 DNA 研究和基因组隐私等方面都有影响。
